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whisper-small-collected-data – AI Model by hoangdeeptry | AlphaNeural AI
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whisper-small-collected-data
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transformers
pytorch
tensorboard
whisper
automatic-speech-recognition
generated_from_trainer
openai/whisper-small
finetune
apache-2.0
endpoints_compatible
us
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whisper-small-collected-data
This model is a fine-tuned version of
openai/whisper-small
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.6221
Wer: 55.5283
Cer: 44.5095
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
learning_rate: 1e-05
train_batch_size: 16
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 2000
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
Cer
0.0069
11.63
1000
0.5614
53.7696
42.3371
0.0011
23.26
2000
0.6221
55.5283
44.5095
Framework versions
Transformers 4.31.0
Pytorch 2.0.0
Datasets 2.14.4
Tokenizers 0.13.3
